Related works: 
Epidemic models have been long studied among many
different fields including mathematical biology
[1]}, computer science [2]},
social science [3]} and so on.
Different epidemic models have been studied in the literature,
but the most common ones include the susceptible-infected-susceptible
(SIS) model and the SIR model.
In the traditional SIS model, the population is divided into
two groups taking
the susceptible and infected states; the ratios of the two groups may
exhibit dynamic behaviors over time.
More recently, the SIS model incorporates networks representing
interactions of agents, where the pandemic process evolves over
time-varying networks [4]}, [5]}, [6]}.
Similar trends can be found in the SIR model, where the agents may
be in susceptible, infected, or recovered state.
Once agents are recovered from their infected states,
they will not be infected again.
Recent works on SIR-type models focus on
improving the model based on real data [7]},
considering time delay issues [8]},
and applying the SIR model in other problems such as
information source detection [9]} and
information epidemics in social networks [10]}.
In [11]}, the development, analysis and
control problems for epidemic models are reviewed from
the viewpoint of systems control.
